Identification of susceptibility modules and hub genes of osteoarthritis by WGCNA analysis

Yanchao Wang; Wenjun Zhou; Yan Chen; Dong He; Zhen Qin; Zhao Wang; Song Liu; Lei Zhou; Jianwen Su; Chi Zhang

doi:10.3389/fgene.2022.1036156

Identification of susceptibility modules and hub genes of osteoarthritis by WGCNA analysis

Front Genet. 2022 Nov 18:13:1036156. doi: 10.3389/fgene.2022.1036156. eCollection 2022.

Authors

Yanchao Wang¹, Wenjun Zhou^{2

3

4}, Yan Chen⁵, Dong He⁶, Zhen Qin⁷, Zhao Wang^{3

4}, Song Liu^{3

4}, Lei Zhou^{2

3

4}, Jianwen Su^{2

3

4}, Chi Zhang^{3

4

8}

Affiliations

¹ Department of Obstetrics and Gynecology, Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
² Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, China.
³ Department of Orthopedics, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
⁴ Department of Joint Surgery, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
⁵ Department of Clinical Laboratory Medicine, the Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
⁶ Department of Neurosurgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
⁷ Department of Clinical Laboratory, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China.
⁸ State Key Laboratory of Respiratory Disease, Translational Research Centre of Regenerative Medicine and 3D Printing Technologies of Guangzhou Medical University, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Abstract

Osteoarthritis (OA) is a major cause of pain, disability, and social burden in the elderly throughout the world. Although many studies focused on the molecular mechanism of OA, its etiology remains unclear. Therefore, more biomarkers need to be explored to help early diagnosis, clinical outcome measurement, and new therapeutic target development. Our study aimed to retrieve the potential hub genes of osteoarthritis (OA) by weighted gene co-expression network analysis (WGCNA) and assess their clinical utility for predicting OA. Here, we integrated WGCNA to identify novel OA susceptibility modules and hub genes. In this study, we first selected 477 and 834 DEGs in the GSE1919 and the GSE55235 databases, respectively, from the Gene Expression Omnibus (GEO) website. Genes with p-value<0.05 and | log₂FC | > 1 were included in our analysis. Then, WGCNA was conducted to build a gene co-expression network, which filtered out the most relevant modules and screened out 23 overlapping WGCNA-derived hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses elucidated that these hub genes were associated with cell adhesion molecules pathway, leukocyte activation, and inflammatory response. In addition, we conducted the protein-protein interaction (PPI) network in 23 hub genes, and the top four upregulated hub genes were sorted out (CD4, SELL, ITGB2, and CD52). Moreover, our nomogram model showed good performance in predicting the risk of OA (C-index = 0.76), and this model proved to be efficient in diagnosis by ROC curves (AUC = 0.789). After that, a single-sample gene set enrichment (ssGSEA) analysis was performed to discover immune cell infiltration in OA. Finally, human primary synoviocytes and immunohistochemistry study of synovial tissues confirmed that those candidate genes were significantly upregulated in the OA groups compared with normal groups. We successfully constructed a co-expression network based on WGCNA and found out that OA-associated susceptibility modules and hub genes, which may provide further insight into the development of pre-symptomatic diagnosis, may contribute to understanding the molecular mechanism study of OA risk genes.

Keywords: SsGSEA; WGCNA; hub genes; osteoarthritis; pathway analysis; protein–protein interaction.